Functions — github.com/RLAgent/gated-path-planning-networks

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Functions85 in github.com/RLAgent/gated-path-planning-networks

⨍ Functions 85 ◇ Types & classes 10

↓ 8 callersFunctionprint_stats

Prints performance statistics output from Runner.

utils/experiment.py:148

↓ 8 callersMethodtest

Tests the model on the given dataset.

utils/runner.py:271

↓ 6 callersFunctioncreate_dataloader

Creates a maze DataLoader. Args: datafile (string): Path to the dataset dataset_type (string): One of "train", "valid", or "test"

utils/experiment.py:101

↓ 4 callersFunction_plot

(train, valid, name)

train.py:82

↓ 4 callersMethod_swap_index

(self, idx1, idx2)

utils/dijkstra.py:62

↓ 4 callersMethodinsert

(self, key, val)

utils/dijkstra.py:16

↓ 4 callersFunctionprint_row

Prints the given items. Args: width (int): Character length for each column. items (list): List of items to print.

utils/experiment.py:128

↓ 3 callersMethod_run

Runs the model on the given data. Args: model (torch.nn.Module): The Planner model dataloader (torch.utils.data.D

utils/runner.py:139

↓ 3 callersFunctionget_mechanism

(mechanism)

utils/experiment.py:87

↓ 3 callersMethodneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:232

↓ 2 callersMethod__init__

(self)

utils/mechanism.py:186

↓ 2 callersMethod_east

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:133

↓ 2 callersMethod_east

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:194

↓ 2 callersMethod_getState

Returns the current state.

utils/maze.py:132

↓ 2 callersMethod_isGoalPos

Returns true if pos is equal to the goal position.

utils/maze.py:128

↓ 2 callersMethod_is_out_of_bounds

(self, maze, p_y, p_x)

utils/mechanism.py:37

↓ 2 callersMethod_north

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:128

↓ 2 callersMethod_north

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:189

↓ 2 callersMethod_northeast

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:209

↓ 2 callersMethod_northwest

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:215

↓ 2 callersMethod_percolate_up

(self, curr_idx)

utils/dijkstra.py:82

↓ 2 callersMethod_south

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:143

↓ 2 callersMethod_south

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:204

↓ 2 callersMethod_southeast

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:220

↓ 2 callersMethod_southwest

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:226

↓ 2 callersMethod_turnleft

(self, p_orient, p_y, p_x)

utils/mechanism.py:65

↓ 2 callersMethod_turnright

(self, p_orient, p_y, p_x)

utils/mechanism.py:61

↓ 2 callersMethod_west

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:138

↓ 2 callersMethod_west

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:199

↓ 2 callersFunctioncreate_dataset

(data_size, compare_mazes=None)

generate_dataset.py:66

↓ 2 callersFunctioncreate_save_dir

Creates and returns path to the save directory.

utils/experiment.py:116

↓ 2 callersMethoddecrease

(self, key, new_val)

utils/dijkstra.py:32

↓ 2 callersFunctiondijkstra_dist

(maze, mechanism, goal)

utils/dijkstra.py:119

↓ 2 callersMethodempty

(self)

utils/dijkstra.py:13

↓ 2 callersMethodextract

(self)

utils/dijkstra.py:44

↓ 2 callersFunctionhash_maze_to_string

(maze)

generate_dataset.py:35

↓ 2 callersMethodinvneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:244

↓ 2 callersFunctionparse_args

()

utils/experiment.py:11

↓ 1 callersMethod_backward

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:69

↓ 1 callersMethod_compute_stats

(self, batch_size, map_design, goal_map, outputs, predictions, labels, loss, opt_p

utils/runner.py:73

↓ 1 callersMethod_forward

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:41

↓ 1 callersMethod_percolate_down

(self, curr_idx)

utils/dijkstra.py:91

↓ 1 callersMethod_process

Data format: list, [train data, test data]

utils/maze.py:29

↓ 1 callersFunctionadd_stack

(next_pos, next_dir)

utils/maze.py:75

↓ 1 callersFunctiondijkstra_policy

(maze, mechanism, goal, policy)

utils/dijkstra.py:156

↓ 1 callersFunctionextract_goal

(goal_map)

generate_dataset.py:59

↓ 1 callersFunctionextract_goal

Returns the goal location.

utils/maze.py:225

↓ 1 callersFunctionextract_policy

Extracts the policy from the given values.

utils/maze.py:198

↓ 1 callersFunctionfmt_item

(x)

utils/experiment.py:135

↓ 1 callersFunctiongenerate_data

(filename, train_size, valid_size, test_size,

generate_dataset.py:18

↓ 1 callersFunctiongenerate_maze

(maze_size, decimation, start_pos=(1, 1))

utils/maze.py:70

↓ 1 callersFunctionget_optimizer

(args, parameters)

utils/runner.py:13

↓ 1 callersFunctionhashed_check_maze_exists

(mazekey, mazehash)

generate_dataset.py:42

↓ 1 callersFunctionmain

()

eval.py:15

↓ 1 callersFunctionmain

()

train.py:25

↓ 1 callersFunctionmain

()

generate_dataset.py:154

↓ 1 callersMethodreset

Resets the maze.

utils/maze.py:153

↓ 1 callersMethodstep

(self, action)

utils/maze.py:188

↓ 1 callersMethodtrain

Trains the model on the given training dataset.

utils/runner.py:257

↓ 1 callersMethodvalidate

Evaluates the model on the given validation dataset. Stores the current model if it achieves the best validation performance.

Args: model (torch.nn.Module): The Planner model mechanism (utils.mechanism.Mechanism): Environment transition kernel

utils/runner.py:30

Method__init__

(self, num_actions, num_orient)

utils/mechanism.py:9

Method__init__

(self)

utils/mechanism.py:32

Method__init__

(self)

utils/mechanism.py:125

Method__init__

Args: filename (str): Dataset filename (must be .npz format). dataset_type (str): One of "train", "valid", or "test".

utils/maze.py:14

Method__init__

(self, mechanism, min_maze_size, max_maze_size,

utils/maze.py:114

Method__init__

(self, num_orient, num_actions, args)

models/GPPN.py:10

Method__init__

(self, num_orient, num_actions, args)

Methodcalc_optimal_and_success

(i)

utils/runner.py:95

Functioncheck_maze_exists

(maze, compare_mazes)

generate_dataset.py:49

Methodforward

(self, map_design, goal_map)

models/GPPN.py:64

Methodforward

(self, map_design, goal_map)

models/VIN.py:62

Methodinvneighbors_func

Computes previous states for each action.

utils/mechanism.py:18

Methodinvneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:96

Methodinvneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:156

Methodneighbors_func

Computes next states for each action.

utils/mechanism.py:14

Methodneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:89

Methodneighbors_func

(self, maze, p_orient, p_y, p_x)

utils/mechanism.py:148

Methodprint_policy

Prints the given policy.

utils/mechanism.py:22

Methodprint_policy

(self, maze, goal, policy)

utils/mechanism.py:103

Methodprint_policy

(self, maze, goal, policy)

utils/mechanism.py:164

Methodprint_policy

(self, maze, goal, policy)

utils/mechanism.py:256